Introduction to Markov chain Monte Carlo ( MCMC ) and its role in modern Bayesian analysisGregory, Phil
Corollary: If P has a limiting distribution π , then every row of Pt converges to π . TIME REVERSIBILITY Time reversibility drives almost any Markov Chain Monte Carlo algorithm. We will define the concept using the stationary distribution of the chain, which we shall show that is meaningful....
1946 年,物理学家 Stanislaw Ulam 在洛斯阿拉莫斯国家实验室研究核武器的项目中,提出了现代版本的马尔可夫链蒙特卡洛方法(Markov Chain Monte Carlo, MCMC),以代替传统的确定性数值算法。并且 Ulam 与同事 von Neumann,Metropolis 提议将这一绝密计划的代号命名为 Monte Carlo,这来源于他那经常借钱赌博的叔叔常去的...
We also comment on how the convergence of a Markov chain to equilibrium can be assessed in practice and provide an illustrating example. Finally, we review some of the freely available, existing software for implementing MCMC methods. Keywords: Monte Carlo simulation; Markov chains; Bayesian ...
1. An Introduction to MCMC 15 Markov chain Monte Carlo (MCMC) algorithms are now widely used in virtually all areas of statistics. In particular, spatial applications featured very prominently in the early development of the methodology (Geman & Geman 1984), and they still provide some of the...
223020 (M22) An introduction to Markov chain Monte Carlo methods and their actuarial applications : Scollnik D.P.M.,: Casualty Actuarial Society, Proceedin... - 《Insurance Mathematics & Economics》 被引量: 0发表: 1998年来源期刊 Insurance Mathematics & Economics 研究点推荐 Monte Carlo methods...
An Introduction to Markov Chain Monte Carlo Teg Grenager July 1, 2004. Seminar on random walks on graphs Lecture No. 2 Mille Gandelsman, Markov Chain Monte Carlo for LDA C. Andrieu, N. D. Freitas, and A. Doucet, An Introduction to MCMC for Machine Learning, R. M. Neal, Probabilistic...
(1973). Optimum Monte Carlo sampling using Markov chains. Biometrika, 60, 607–612. Article MathSciNet MATH Google Scholar Rosenthal, J.S. (1995). Minorization conditions and convergence rates for Markov chain Monte Carlo. J. Amer. Statist. Assoc., 90, 558–566. Article MathSciNet MATH ...
The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored incl... (展开全部) 作者简介 ··· Joseph K. Blitzstein, PhD, professor of the practice in statis...
doi:10.1093/pan/mph021MONTE Carlo methodMARKOV processesAn introduction to the journal is presented, in which the editor discusses an article on Bayesian statistics, the application Markov chain Monte Carlo (MCMC), and social science methodology.Political AnalysisGill, Jeff...